Abstract
ABSTRACT A grey-box modelling incorporating mechanism and data is presented in this paper to predict the ship manoeuvering motion. The traditional mathematical model in three degrees of freedom is adopted to reveal the known movement mechanism, in which an additional hydrodynamic correction term is developed by Neural Network (NN) based on the data to adaptively estimate the errors induced by the idealised approximation. The KRISO Container Ship (KCS) is taken as the study object and the free-running model tests are carried out to obtain the data for establishing the NN model of hydrodynamic correction terms. The typical manoeuvers (tactical circles, zigzags, Williamson turns) are simulated by the grey-box model and the mathematical model, respectively. The results indicate that the grey-box modelling method proposed in this paper can not only improve the prediction accuracy but also demonstrate a good generalisation performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
